Post Doctoral Fellow

Who is Saint Louis University? Founded in 1818, Saint Louis University is one of the nation’s oldest and most prestigious Catholic universities. SLU, which also has a campus in Madrid, Spain, is recognized for world-class academics, life-changing research, compassionate health care, and a strong commitment to faith and service.

Postdoctoral Fellow – Computational Biology / Bioinformatics Focus: Multi-omics and Longitudinal Modeling in Alzheimer’s Disease Appointment: Full-time, 1-year term (renewable pending funding and performance)

Position Overview We are seeking a highly motivated Postdoctoral Fellow with a PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, or a related quantitative field to join an interdisciplinary research program focused on Alzheimer’s disease (AD) and neurodegeneration.

The fellow will lead and contribute to advanced bioinformatics, multi-omics integration, and statistical modeling efforts using large, well-phenotyped longitudinal datasets (e.g., proteomics, transcriptomics, imaging, clinical, and biomarker data). The position is ideal for a candidate interested in mechanistic discovery, biomarker development, and translational neuroscience, with opportunities for high-impact publications and grant development.

Key Responsibilities Perform computational analysis of large-scale omics datasets, including proteomics, transcriptomics, and related modalities

Integrate multi-omics data with clinical, cognitive, and imaging phenotypes in longitudinal cohorts

Develop and apply statistical and machine-learning models (e.g., mixed-effects models, survival analysis, dimensionality reduction, clustering, trajectory modeling)

Lead reproducible analysis pipelines in R, Python, or related frameworks

Interpret results in biological and clinical context, with emphasis on Alzheimer’s disease mechanisms and biomarkers

Prepare figures, tables, and methods for peer-reviewed manuscripts and conference presentations

Collaborate with clinicians, wet-lab scientists, and biostatisticians in an interdisciplinary environment

Contribute to grant proposals and progress reports as appropriate

Mentor graduate or undergraduate trainees in computational methods (optional, depending on interest)

Required Qualifications PhD in Computational Biology, Bioinformatics, Biostatistics, Data Science, Systems Biology, or a related quantitative discipline

Strong experience with high-dimensional biological data analysis

Proficiency in R and/or Python for statistical computing and data analysis

Solid foundation in statistics and data modeling, particularly for longitudinal or cohort-based data

Demonstrated ability to work independently and manage complex datasets

Strong written and verbal communication skills in English

Evidence of productivity (e.g., peer-reviewed publications, preprints, or advanced projects)

Preferred Qualifications

• Experience with longitudinal modeling (e.g., mixed-effects models, disease progression modeling)

• Familiarity with neurodegenerative disease research, Alzheimer’s disease, or aging biology

• Experience with proteomics platforms (e.g., Olink, SomaScan, mass spectrometry)

• Knowledge of multi-omics integration, network analysis, or pathway enrichment methods

• Experience working with large consortium datasets (e.g., ADNI, AMP-AD, UK Biobank, similar)

• Interest in translational research, biomarker discovery, or drug target identification

• Experience with reproducible research practices (version control, documentation, workflow tools)

• Environment & Opportunities The fellow will join a highly collaborative research environment at the interface of neurology, neuroscience, and computational biology, with access to rich datasets and strong clinical context. The position offers: Intellectual ownership of projects

• Opportunities for first-author publications

• Exposure to grant writing and translational research strategy

• Career mentorship tailored to academic, industry, or hybrid career paths

• Term & Compensation One-year appointment with possibility of renewal based on funding and performance

• Competitive salary and benefits commensurate with experience and institutional guidelines

• Application Instructions: Applicants should submit: 1) Curriculum vitae 2) Brief cover letter describing research interests and relevant experience 3) Contact information for 2–3 references

• Grant-funded Post-Doctoral appointments may be terminated if grant funding ends.

• This position does not currently sponsor J1, H1B, or O visas.

• Function

• Research Support

• Scheduled Weekly Hours: 40

Saint Louis University is an equal opportunity/affirmative action employer. All qualified candidates will receive consideration for the position applied for without regard to race, color, religion, sex, age, national origin, disability, marital status, sexual orientation, military/veteran status, gender identity, or other non-merit factors. If accommodations are needed for completing the application and/or with the interviewing process, please contact Human Resources at 314-977-5847.